A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

https://code.visualstudio.com/docs/remote/faq#_can-i-run-vs-code-server-on-older-linux-distributions

The above "documentation" appears to be untested or verified. So here's an attempt to actually make crosstool-NG actually work.

• docker with buildx
• PermitUserEnvironment yes in /etc/ssh/sshd_config

If checkout shows errors like "Payment not approved" or similar, try converting the short payment link into the full URL version first.

1. Open the checkout page

2. Press F12

3. Go to Console

4. Type allow pasting and press Enter if Chrome blocks paste

Ghostty + Zoxide + Yazi + Oh-My-Zsh 完整配置

• Ghostty - 现代化 GPU 加速终端模拟器
• Zoxide - 智能目录跳转工具（cd 的智能替代）
• Yazi - 快速终端文件管理器
• Oh-My-Zsh - Zsh 配置框架

curl -su "3nVuSoBZnx6U4vzUxf5w:Bcs59EFbbsdF6Sl9Ng71smgStWEGwXXKSjYvPVt7qys" -d "grant_type=client_credentials" "https://api.twitter.com/oauth2/token"

{
  "token_type": "bearer",
  "access_token": "AAAAAAAAAAAAAAAAAAAAAFXzAwAAAAAAMHCxpeSDG1gLNLghVe8d74hl6k4%3DRUMF4xAQLsbeBhTSRrCiQpJtxoGWeyHrDb5te2jpGskWDFW82F"
}